(c) Simulated medical imaging.
Synthetic image data is commonly used to improve performance on downstream ML tasks such as in medical imaging [1]}, [2]}, [3]}.
We simulate a scenario where hospitals serving different populations share patients' data indirectly to improve predictions on medical imaging classification tasks on the whole population using the real-world MNIST [4]} and CIFAR-10 [5]} image datasets as surrogates. Synthetic data are obtained by sampling from pre-trained MMD GANs [6]}. We perform dimensionality reduction on the surrogate MNIST and CIFAR-10 image datasets to create 8-D datasets, detailed in Appendix .
